Matt Richfield is a seasoned data science leader blending rigorous research training with hands-on product delivery, currently a Senior Data Scientist at Getty Images and a Lecturer at Northeastern University in Seattle. He excels at building robust data science ecosystems, from Flask-based ML platforms deployed via Azure CI/CD to scalable forecasting frameworks powering large inventories. At Shelf Engine, he led a cross-functional team to refactor production forecasting, deploying a greenfield ML ecosystem and a Python framework that unified training and deployment, delivering a $1.3M annual savings and reducing inventory discrepancies across 100k SKU locations. As a Tech Lead at Glue and a Data Science Manager at Shelf Engine, he has defined roadmaps, owned OKRs, and steered sprint processes to align data, product, and operations. His foundation is deep in chemical engineering (BS, MS, PhD from UIUC and UC Berkeley), and he brings an experimental, rigor-first mindset to machine learning and experimentation. Based in Seattle, he combines enterprise-scale data science leadership with startup agility to translate complex requirements into practical, auditable solutions.
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